An on-device seq2seq model needs to meet the computation and memory requirement discussed in Section REF ; furthermore, we expect the model to achieve as good results as possible. For a standard Transformer [1]}, we observe the model of 512 dimension can basically meet the FLOPS requirement (2G FLOPS), as shown in Table REF ; and its variant [2]} with a deep encoder and a shallow decoder allows the model to decode faster in practice at test time despite slightly more FLOPS.
